Detectors

By default, Frigate will use a single CPU detector. If you have a Coral, you will need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras.

Frigate supports edgetpu and cpu as detector types. The device value should be specified according to the Documentation for the TensorFlow Lite Python API.

Note: There is no support for Nvidia GPUs to perform object detection with tensorflow. It can be used for ffmpeg decoding, but not object detection.

Single USB Coral#

detectors:
  coral:
    type: edgetpu
    device: usb

Multiple USB Corals#

detectors:
  coral1:
    type: edgetpu
    device: usb:0
  coral2:
    type: edgetpu
    device: usb:1

Native Coral (Dev Board)#

warning: may have compatibility issues after v0.9.x

detectors:
  coral:
    type: edgetpu
    device: ""

Multiple PCIE/M.2 Corals#

detectors:
  coral1:
    type: edgetpu
    device: pci:0
  coral2:
    type: edgetpu
    device: pci:1

Mixing Corals#

detectors:
  coral_usb:
    type: edgetpu
    device: usb
  coral_pci:
    type: edgetpu
    device: pci

CPU Detectors (not recommended)#

detectors:
  cpu1:
    type: cpu
    num_threads: 3
  cpu2:
    type: cpu
    num_threads: 3

When using CPU detectors, you can add a CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.